Development and validation of a radiomics signature as a non-invasive complementary predictor of gastroesophageal varices and high-risk varices in compensated advanced chronic liver disease: A multicenter study

Cystatin C/albumin ratio for early diagnosis of esophageal varices in liver cirrhosis

The mortality rate related to variceal bleeding is high in patients with liver cirrhosis. Early detection and treatment of varices can reduce the risk of hemorrhage and thus decrease the mortality rate related to variceal bleeding. The study comprised 81 cirrhotic patients in training set, who were categorized into 2 groups: the patients with esophageal varices (EVs group) and the patients without esophageal varices (non-EVs group). The disparity in Cystatin C/albumin ratio (CAR) was assessed between these 2 groups. Subsequently, a regression model was constructed by generating a receiver operating characteristic (ROC) curve to calculate the area under the curve (AUC). Then an external validation was performed in 25 patients. Among patients with cirrhosis in training set, a statistically significant difference in CAR was observed between the EVs group and non-EVs group (P < .05). At the CAR cutoff value of 2.79*10-5, the AUC for diagnosing EVs were 0.666. Further, a multivariate logistic regression model was constructed, after adjusting the model, the AUC for EVs diagnosis were 0.855. And the external validation showed that the model could not be considered as a poor fit. CAR exhibits potential as an early detection marker for EVs in liver cirrhosis, and the regression model incorporating CAR demonstrates a strong capability for early EVs diagnosis.

Chinese consensus on the management of liver cirrhosis

Liver cirrhosis, characterized by diffuse necrosis, insufficient regeneration of hepatocytes, angiogenesis, severe fibrosis, and the formation of pseudolobules, is a progressive, chronic liver disease induced by a variety of causes. It is clinically characterized by liver function damage and portal hypertension, and many complications may occur in its late stage. Based on the updated practice guidelines, expert consensuses, and research advances on the diagnosis and treatment of cirrhosis, the Chinese Society of Gastroenterology of Chinese Medical Association established the current consensus to standardize the clinical diagnosis and management of liver cirrhosis and guide clinical practice. This consensus contains 43 statements on the etiology, pathology and pathogenesis, clinical manifestations, major complications, diagnosis, treatment, prognosis, and chronic disease control of liver cirrhosis. Since several practice guidelines and expert consensuses on the complications of liver cirrhosis have been published, this consensus emphasizes the research progress of liver cirrhosis itself.

Endoscopic Ruler for varix size measurement: A multicenter pilot study

BACKGROUND

We invented Endoscopic Ruler, a new endoscopic device to measure the size of varices in patients with cirrhosis and portal hypertension.

AIM

To assess the feasibility and safety of Endoscopic Ruler, and evaluate the agreement on identifying large oesophageal varices (OV) between Endoscopic Ruler and the endoscopists, as well as the interobserver agreement on diagnosing large OV using Endoscopic Ruler.

METHODS

We prospectively and consecutively enrolled patients with cirrhosis from 11 hospitals, all of whom got esophagogastroduodenoscopy (EGD) with Endoscopic Ruler. The primary study outcome was a successful measurement of the size of varices using Endoscopic Ruler. The secondary outcomes included adverse events, operation time, the agreement of identifying large OV between the objective measurement of Endoscopic Ruler and the empirical reading of endoscopists, together with the interobserver agreement on diagnosing large OV by Endoscopic Ruler.

RESULTS

From November 2020 to April 2022, a total of 120 eligible patients with cirrhosis were recruited and all of them underwent EGD examinations with Endoscopic Ruler successfully without any adverse event. The median operation time of Endoscopic Ruler was 3.00 min [interquartile range (IQR): 3.00 min]. The kappa value between Endoscopic Ruler and the endoscopists while detecting large OV was 0.52, demonstrating a moderate agreement. The kappa value for diagnosing large OV using Endoscopic Ruler among the six independent observers was 0.77, demonstrating a substantial agreement.

CONCLUSION

The data demonstrates that Endoscopic Ruler is feasible and safe for measuring the size of varices in patients with cirrhosis and portal hypertension. Endoscopic Ruler is potential to promote the clinical practice of the two-grade classification system of OV.

Development and validation of a machine learning-based model for varices screening in compensated cirrhosis (CHESS2001): an international multicenter study

BACKGROUND AND AIMS

The prevalence of high-risk varices (HRV) is low among compensated cirrhotic patients undergoing EGD. Our study aimed to identify a novel machine learning (ML)-based model, named ML EGD, for ruling out HRV and avoiding unnecessary EGDs in patients with compensated cirrhosis.

METHODS

An international cohort from 17 institutions from China, Singapore, and India were enrolled (CHESS2001). The variables with the top 3 importance scores (liver stiffness, platelet count, and total bilirubin) were selected by the Shapley additive explanation and input into a light gradient-boosting machine algorithm to develop ML EGD for identification of HRV. Furthermore, we built a web-based calculator for ML EGD, which is free with open access (http://www.pan-chess.cn/calculator/MLEGD_score). Unnecessary EGDs that were not performed and the rates of missed HRV were used to assess the efficacy and safety for varices screening.

RESULTS

Of 2794 enrolled patients, 1283 patients formed a real-world cohort from 1 university hospital in China used to develop and internally validate the performance of ML EGD for varices screening. They were randomly assigned into the training (n = 1154) and validation (n = 129) cohorts with a ratio of 9:1. In the training cohort, ML EGD spared 607 (52.6%) unnecessary EGDs with a missed HRV rate of 3.6%. In the validation cohort, ML EGD spared 75 (58.1%) EGDs with a missed HRV rate of 1.4%. To externally test the performance of ML EGD, 966 patients from 14 university hospitals in China (test cohort 1) and 545 from 2 hospitals in Singapore and India (test cohort 2) comprised the 2 test cohorts. In test cohort 1, ML EGD spared 506 (52.4%) EGDs with a missed HRV rate of 2.8%. In test cohort 2, ML EGD spared 224 (41.1%) EGDs with a missed HRV rate of 3.1%. When compared with the Baveno VI criteria, ML EGD spared more screening EGDs in all cohorts (training cohort, 52.6% vs 29.4%; validation cohort, 58.1% vs 44.2%; test cohort 1, 52.4% vs 26.5%; test cohort 2, 41.1% vs 21.1%, respectively; P < .001).

CONCLUSIONS

We identified a novel model based on liver stiffness, platelet count, and total bilirubin, named ML EGD, as a free web-based calculator. ML EGD could efficiently help rule out HRV and avoid unnecessary EGDs in patients with compensated cirrhosis. (Clinical trial registration number: NCT04307264.).

Artificial Intelligence in Hepatology- Ready for the Primetime

Artificial Intelligence (AI) is a mathematical process of computer mediating designing of algorithms to support human intelligence. AI in hepatology has shown tremendous promise to plan appropriate management and hence improve treatment outcomes. The field of AI is in a very early phase with limited clinical use. AI tools such as machine learning, deep learning, and 'big data' are in a continuous phase of evolution, presently being applied for clinical and basic research. In this review, we have summarized various AI applications in hepatology, the pitfalls and AI's future implications. Different AI models and algorithms are under study using clinical, laboratory, endoscopic and imaging parameters to diagnose and manage liver diseases and mass lesions. AI has helped to reduce human errors and improve treatment protocols. Further research and validation are required for future use of AI in hepatology.

A strategy for varices screening based on acoustic radiation force impulse combined with platelet (CHESS2001): An alternative of Baveno VI criteria

Few studies have reported on acoustic radiation force impulse (ARFI) for varices screening. Our study aimed to identify a strategy based on liver stiffness measurement (LSM) and spleen stiffness measurement (SSM) by ARFI combined with platelet count (PLT), named the ARP strategy, for ruling out high-risk varices (HRV) and avoiding unnecessary esophagogastroduodenoscopy (EGD) in patients with compensated cirrhosis. We retrospectively reviewed patients who underwent ARFI from a previous cohort (NCT04307264). Of them, patients between 2017 and 2019 composed the training cohort to develop the ARP strategy. The validation cohort consisted of others between 2015 and 2016 to validate and compare it with Baveno VI criteria about the performance for varices screening. Primary outcomes were the rates of spared EGDs and HRV missed. A total of 741 consecutive patients were included in the final analysis. Of them, 576 patients were included in the training cohort and 165 patients in the validation cohort. In the training cohort, ARP strategy was defined as LSM < 1.805 m/s or SSM < 2.445 m/s and PLT > 110 × 109 /L. ARP strategy could spare 234 (40.6%) EGDs with a missed HRV rate of 3.4% (8 of 234). In the validation cohort, compared with Baveno VI criteria, the ARP strategy improved the proportion of avoided EGDs (49.7% vs. 34.5%; p < 0.001) and lowered the rate of misclassified HRV (1.2% vs. 3.5%; p < 0.001). Conclusion: The ARP strategy was an efficient and safe tool for varices screening in compensated cirrhosis, and it might be an auxiliary or even alternative to Baveno VI criteria.

Small varices in chronic liver diseases

PURPOSE OF REVIEW

Gastroesophageal varices are common complications of chronic liver diseases (CLDs) and portal hypertension. Small varices have the risk of progressing to larger varices, causing bleeding or even death. Thus, early detection and appropriate management of small varices are necessary. The purpose of this review is to summarize the advance in the recent 5years about diagnosing and managing the small varices in CLDs.

RECENT FINDINGS

The diagnosing methods of small varices in recent studies include improved endoscopic examinations, such as capsule endoscopy, and many noninvasive methods, including blood tests, ultrasound, computed tomography and magnetic resonance. For the management of small varices, though it is controversial, prevention using nonselective beta-blockers is still an essential part.

SUMMARY

In this review, we summarize the classification of varices, the invasive and noninvasive diagnostic methods, their performances, and the emerging progression in the management of small varices in the recent 5 years. We hope that this review provides relevant information to understand better and appropriately manage small varices.

Treatment Strategies in Emergency Endoscopy for Acute Esophageal Variceal Bleeding (CHESS1905): A Nationwide Cohort Study

BACKGROUND AND AIMS

Emergency endoscopy is recommended for patients with acute esophageal variceal bleeding (EVB) and their prognosis has improved markedly over past decades due to the increased specialization of endoscopic practice. The study aimed to compare outcomes following emergency endoscopic injection sclerotherapy (EIS) and endoscopic variceal ligation (EVL) in cirrhotic patients with acute EVB.

METHODS

Cirrhotic patients with acute EVB who underwent emergency endoscopy were retrospectively enrolled from 2013 to 2020 across 34 university hospitals from 30 cities. The primary outcome was the incidence of 5-day rebleeding after emergency endoscopy. Subgroup analysis was stratified by Child-Pugh class and bleeding history. A 1:1 propensity score matching (PSM) analysis was performed.

RESULTS

A total of 1,017 and 382 patients were included in EIS group and EVL group, respectively. The 5-day rebleeding incidence was similar between EIS group and EVL group (4% vs. 5%, P = 0.45). The result remained the same after PSM (P = 1.00). Among Child-Pugh class A, B and C patients, there were no differences in the 5-day rebleeding incidence between the two groups after PSM (P = 0.25, 0.82, and 0.21, respectively). As for the patients with or without bleeding history, the differences between EIS group and EVL group were not significant after PSM (P = 1.00 and 0.26, respectively).

CONCLUSION

The nationwide cohort study indicates that EIS and EVL are both efficient emergency endoscopic treatment strategies for acute EVB. EIS should not be dismissed as an economical and effective emergency endoscopic treatment strategy of acute EVB. ClincialTrials.gov number NCT04307264.

Artificial intelligence in the diagnosis of cirrhosis and portal hypertension

Clinically significant portal hypertension is associated with an increased risk of developing gastroesophageal varices and hepatic decompensation. Hepatic venous pressure gradient measurement and esophagogastroduodenoscopy are the gold-standard methods for assessing clinically significant portal hypertension and gastroesophageal varices, respectively. However, invasiveness, cost, and feasibility limit their widespread use, especially if repeated and serial evaluations are required to assess the efficacy of pharmacotherapy. Artificial intelligence describes a range of techniques that allow machines to perform tasks typically thought to require human reasoning and problem-solving skills. Artificial intelligence has made great strides in the field of medicine, and is also involved in portal hypertension diagnosis. Artificial intelligence tools will potentially transform our practice by leveraging massive amounts of data to personalize care to the right patient, in the right amount, at the right time. This review focuses on the recent advances in artificial intelligence for the noninvasive diagnosis of portal hypertension and gastroesophageal varices and monitoring of risk assessment of its complications in clinical practice.

A novel radiomics-platelet nomogram for the prediction of gastroesophageal varices needing treatment in cirrhotic patients

BACKGROUND AND AIMS

Highly accurate noninvasive methods for predicting gastroesophageal varices needing treatment (VNT) are desired. Radiomics is a newly emerging technology of image analysis. This study aims to develop and validate a novel noninvasive method based on radiomics for predicting VNT in cirrhosis.

METHODS

In this retrospective-prospective study, a total of 245 cirrhotic patients were divided as the training set, internal validation set and external validation set. Radiomics features were extracted from portal-phase computed tomography (CT) images of each patient. A radiomics signature (Rad score) was constructed with the least absolute shrinkage and selection operator algorithm and tenfold cross-validation in the training set. Combined with independent risk factors, a radiomics nomogram was built with a multivariate logistic regression model.

RESULTS

The Rad score, consisting of 14 features from the gastroesophageal region and 5 from the splenic hilum region, was effective for VNT classification. The diagnostic performance was further improved by combining the Rad score with platelet counts, achieving an AUC of 0.987 (95% CI 0.969-1.00), 0.973 (95% CI 0.939-1.00) and 0.947 (95% CI 0.876-1.00) in the training set, internal validation set and external validation set, respectively. In efficacy and safety assessment, the radiomics nomogram could spare more than 40% of endoscopic examinations with a low risk of missing VNT (< 5%), and no more than 8.3% of unnecessary endoscopic examinations still be performed.

CONCLUSIONS

In this study, we developed and validated a novel, diagnostic radiomics-based nomogram which is a reliable and noninvasive method to predict VNT in cirrhotic patients.

CLINICAL TRIALS REGISTRATION

NCT04210297.

Radiomics and deep learning in liver diseases

Recently, radiomics and deep learning have gained attention as methods for computerized image analysis. Radiomics and deep learning can perform diagnostic or predictive tasks using high-dimensional image-derived features and have the potential to expand the capabilities of liver imaging beyond the scope of traditional visual image analysis. Recent research has demonstrated the potential of these techniques in various fields of liver imaging, including staging of liver fibrosis, prognostication of malignant liver tumors, automated detection and characterization of liver tumors, automated abdominal organ segmentation, and body composition analysis. However, because most of the previous studies were preliminary and focused mainly on technical feasibility, further clinical validation is required for the application of radiomics and deep learning in clinical practice. In this review, we introduce the technical aspects of radiomics and deep learning and summarize the recent studies on the application of these techniques in liver radiology.

Artificial intelligence in liver disease

Artificial intelligence (AI) is a branch of computer science that attempts to mimic human intelligence, such as learning and problem-solving skills. The use of AI in hepatology occurred later than in gastroenterology. Nevertheless, studies on applying AI to liver disease have recently increased. AI in hepatology can be applied for detecting liver fibrosis, differentiating focal liver lesions, predicting prognosis of chronic liver disease, and diagnosing of nonalcoholic fatty liver disease. We expect that AI will eventually help manage patients with liver disease, predict the clinical outcomes, and reduce medical errors. However, there are several hurdles that need to be overcome. Here, we will briefly review the areas of liver disease to which AI can be applied.